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Myths and Mathemagical Superpowers of Data Scientists

Some people think data scientists are mythical beings, like unicorns, or they are some sort of nouveau fad that will quickly fade. Not true, says IBM big data evangelist James Kobielus. In this engaging presentation, with artwork created by Angela Tuminello, Kobielus debunks 10 myths about data scientists and their role in analytics and big data. You might also want to read the full blog by Kobielus that spawned this presentation: "Data Scientists: Myths and Mathemagical Superpowers" - http://ibm.co/PqF7Jn

7.
Data scientists get their fingernails dirty dumping piles of data into analytical sandboxes, cleansing, and sifting through it for usefulpatterns that may or may not exist. Then, they do it all over again. Reality #2 IBMbigdatahub.com

8.
Data scientists get their fingernails It’s ofte nu piles n mind- into dirty dumpingm bingly of data analytical sandboxes, detailed grunt cleansing, the sp work, ort of a n useful and sifting through it for ot rm data por may chairexist.patterns that may hiloso not phers. Then, they do it all over again. Reality #2 IBMbigdatahub.com

10.
The term “data scientist” has beenaround for years, and the various advanced analytics specialties that fall under it are even older.Recently, the term has been used in the convergence of disciplines that have become super-hot. Reality #3 IBMbigdatahub.com

11.
The term “data scientist” has beenaround for years, and the various advanced analytics specialties that fall growth under n job iit are even older. Ste ady the academic been usedRecently,and term has. st i ngs iable unden lithe convergence of disciplines in ricula is c ur fad. that Thi s is no have become super-hot. Reality #3 IBMbigdatahub.com

12.
Myth #4Data scientists are all just PhD statisticians who failed to make tenure.

13.
Many data scientists acquired their quantitative and statistical modeling skills in college, but pursued degrees in business administration, economics andengineering. They actually know about business problems. Reality #4 IBMbigdatahub.com

22.
The job of the data scientists is to look for hidden patterns. They canaccomplish this through user-friendly visualization tools, search-driven BI tools and other approaches that don’t require a deep mastery of statistical analysis. Reality #7 IBMbigdatahub.com

27.
Myth #9 Data scientists are analyticsjunkies who couldn’t care less about business applications.

28.
If you spend time with any real- world data scientist, they’ll bend your ear discussing how theytackled a specific business problem, such as reducing customer churn, targeting offers across channels, and mitigating financial risks. Reality #9 IBMbigdatahub.com

30.
Myth #10Data scientists don’t have anyresponsibilities that force them out of their ivory towers.

31.
That used to be the case. However, as next best action and real-worldexperiments become ubiquitous, the data scientist is evolving into the role that stokes, tweaks and fuels the operational engine. Reality #10 IBMbigdatahub.com

32.
That used to be the case. However, Da best action and real-world as nextta scien analy tists te s the tic become t ubiquitous, theexperiments- cent at the ric mo dels data scientistrt oevolving into the hea is busine f agile ss pro tweaks and fuels role that stokes,cess es. the operational engine. Reality #10 IBMbigdatahub.com

33.
For more from James Kobielus and other big data thought leaders, visit The Big Data Hub at IBMbigdatahub.com